Journal
ECOLOGICAL INDICATORS
Volume 11, Issue 2, Pages 715-723Publisher
ELSEVIER
DOI: 10.1016/j.ecolind.2010.05.005
Keywords
Agro-environmental indicators; Fertilisation management; GIS-based spatial analysis; Gross nutrient balance; Po river plain; Territorial scale
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Funding
- Regione Piemonte, Assessorato Agricoltura Tutela della Fauna e della Flora
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Regionally mandated budgets often ignore important sub-regional differences. To help identify hot-spots, where environmental pressures and agricultural activities combine and heighten the need to optimise farming strategies, we recommend using detailed spatial target analysis. In this paper, we propose a methodology for identifying different agro-environments, test that method in a case-study territory in the western Po River plain (the largest and most intensive agricultural area in Italy), and then calculate the nutrient budget indicators of these defined agro-environments as a means to assess environmental sustainability. We identified five Macro Land Units (MLUs) representing five different agro-environments from official datasets and territorial surveys, detected and quantified land use, crop productivity, and fertilisation management in these MLUs, and calculated nutrient budgets according to the IRENA European methodology. As expected, the highest nutrient surpluses (103, 39, and 95 kg ha(-1) for N, P. and K, respectively) were detected in the most intensely managed area. N surpluses were attributed to excess mineral inputs and P surpluses to excess organic inputs. At the territorial scale, the manure N load was far below the 170 kg ha(-1) threshold; at the crop scale, maize showed the least-optimised fertilisation management. This work suggests that GIS-based analysis of environmental pressures of agricultural activities at a sub-regional level is useful for identifying areas and crops for which fertilization must be well managed. The proposed methodology depends on accurate collection and collation of farm data into GIS databases; public authorities should promote investment in planning and managing data collection in agriculture. (C) 2010 Elsevier Ltd. All rights reserved.
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